During the use of robotics in applications such as antiterrorism or combat,a motion-constrained pursuer vehicle,such as a Dubins unmanned surface vehicle(USV),must get close enough(within a prescribed zero or positive...During the use of robotics in applications such as antiterrorism or combat,a motion-constrained pursuer vehicle,such as a Dubins unmanned surface vehicle(USV),must get close enough(within a prescribed zero or positive distance)to a moving target as quickly as possible,resulting in the extended minimum-time intercept problem(EMTIP).Existing research has primarily focused on the zero-distance intercept problem,MTIP,establishing the necessary or sufficient conditions for MTIP optimality,and utilizing analytic algorithms,such as root-finding algorithms,to calculate the optimal solutions.However,these approaches depend heavily on the properties of the analytic algorithm,making them inapplicable when problem settings change,such as in the case of a positive effective range or complicated target motions outside uniform rectilinear motion.In this study,an approach employing a high-accuracy and quality-guaranteed mixed-integer piecewise-linear program(QG-PWL)is proposed for the EMTIP.This program can accommodate different effective interception ranges and complicated target motions(variable velocity or complicated trajectories).The high accuracy and quality guarantees of QG-PWL originate from elegant strategies such as piecewise linearization and other developed operation strategies.The approximate error in the intercept path length is proved to be bounded to h2/(4√2),where h is the piecewise length.展开更多
Every year, around the world, between 250,000 and 500,000 people suffer a spinal cord injury(SCI). SCI is a devastating medical condition that arises from trauma or disease-induced damage to the spinal cord, disruptin...Every year, around the world, between 250,000 and 500,000 people suffer a spinal cord injury(SCI). SCI is a devastating medical condition that arises from trauma or disease-induced damage to the spinal cord, disrupting the neural connections that allow communication between the brain and the rest of the body, which results in varying degrees of motor and sensory impairment. Disconnection in the spinal tracts is an irreversible condition owing to the poor capacity for spontaneous axonal regeneration in the affected neurons.展开更多
It is important for a lunar lander to possess a large divert capability during the final landing phase,as this can enhance the tolerance for flight deviations in the early phase or improve the obstacle avoidance perfo...It is important for a lunar lander to possess a large divert capability during the final landing phase,as this can enhance the tolerance for flight deviations in the early phase or improve the obstacle avoidance performance.Therefore,when designing the powered descent trajectory,sufficient final phase divert capability should be reserved at the minimum propellant cost.To this end,a multi-phase trajectory programming(MPTP)method for powered descent with approaching phase divert capability is proposed.First,the entire powered descent trajectory is divided into the main braking phase and the approaching phase.The main braking phase is responsible for dissipating the majority of the initial velocity.The approaching phase is responsible for safely and precisely flying toward the landing site.It is nominally a vertical descent trajectory and possesses equal divert capability in all horizontal directions.Then,a constant-thrust linear tangent guidance(LTG)accounting for the lunar curvature is designed for the main braking phase.For the approaching phase,a variable-thrust lossless convex programming(LCP)guidance considering the constraints of tilt angle and glide-slope angle is developed.Subsequently,to connect the two phases and further optimize the propellant consumption throughout the entire trajectory,a method for determining the phase switching condition is proposed.The originally difficult-to-solve two-parameter optimization problem is decomposed into two more easily solvable subproblems,which are solved iteratively via a bilevel optimization framework.Finally,the divert capability of the proposed method is verified through numerical simulation.The programmed trajectory is basically consistent with the results of the pseudospectral method,with the difference in propellant consumption being only 0.006%.This method is suitable for the rapid iterative design of nominal trajectories for lunar lander powered descent in engineering applications.展开更多
This paper delves into the H∞optimal output regulation problem for continuous-time linear systems with an unknown system model.By integrating the internal model principle with optimal control,we derive an optimal con...This paper delves into the H∞optimal output regulation problem for continuous-time linear systems with an unknown system model.By integrating the internal model principle with optimal control,we derive an optimal control policy and a worst-case disturbance policy through the formulation and solution of a zero-sum game problem.Subsequently,leveraging adaptive dynamic programming,we propose a policy iteration learning algorithm capable of learning both the optimal control policy and the worst-case disturbance policy directly from system data.The existing algorithms necessitate an initial stabilizing policy,a full-rank condition,and the storage of historical data to guarantee algorithm convergence.In contrast,we design a dual policy iteration algorithm equipped with an online learning mechanism,thereby eliminating these additional prerequisites.Simulation results with an antonomous ground vehicle underscore the effectiveness of our proposed algorithm,and its superiority is further demonstrated through comparisons with existing methodologies.展开更多
The operational demands of a wide range significantly exacerbate combustion instability issues within ramjet combustor.To suppress combustion oscillations,an open-loop control system utilizing Linear Genetic Programmi...The operational demands of a wide range significantly exacerbate combustion instability issues within ramjet combustor.To suppress combustion oscillations,an open-loop control system utilizing Linear Genetic Programming(LGP)has been developed for a full-scale annular ramjet combustor.The LGP is used to generate control laws that include multi-frequency forcing.These laws are then transformed into square waves to actuate the solenoid valve,which modulates the kerosene supply for open-loop control.The results show that the duty cycle has little effect on instability amplitude,whereas an increase in frequency leads to a remarked reduction in combustion amplitude.After five generations evolvements,the pressure amplitude is reduced by 40.6% under the optimal control law generated by LGP.Furthermore,the machine learning process is depicted using a proximity map of control law similarity,with the search pathway visualized by the steepest descent.All individuals go forward to the upper left corner of the map with the evolution process,terminating at the optimal individual of the fifth generation.展开更多
Natural convection in enclosures containing nanofluids has attracted significant attention due to its relevance in thermal management systems.In this context,this study presents a comprehensive numerical investigation...Natural convection in enclosures containing nanofluids has attracted significant attention due to its relevance in thermal management systems.In this context,this study presents a comprehensive numerical investigation of flow and heat transfer in a square cavity saturated with water-based CuO nanofluid having a centrally placed sinusoidal-shaped heated element.All the enclosure walls satisfy the no-slip velocity condition.Thermally,the vertical walls are kept at a cold reference temperature,the lower wall is partially heated at its center,and the remaining portions of the lower and entire upper walls are adiabatic.The internal sinusoidal element is also uniformly heated.The flow dynamics and thermal fields are governed by the two-dimensional steady-state Navier-Stokes and energy equations,solved using the Galerkin finite element method.Additionally,a novel hybrid approach integrating multi-expression programming(MEP)technique with a convolutional neural network bidirectional gated recurrent unit(CNN-BiGRU)deep learning network is also applied to enhance flow and thermal prediction accuracy.This hybrid approach enables precise evaluation of how heater waviness,magnetic field orientation,and nanoparticle dispersion influence flow structure and heat transfer.Results reveal stronger convection at high Rayleigh numbers,magnetic damping at increased Hartmann numbers,and higher temperatures with reduced velocity at greater nanoparticle concentrations.Among the analyzed situations,increasing heater waviness improves heat-transfer performance.Both the MEP and CNN-BiGRU models accurately capture the key features of flow and heat transport trends,indicating that the hybrid approach provides enhanced predictive capability for complex convection-driven nanofluid systems.展开更多
This paper proposes a hybrid sequential second-order cone programming(HSSOCP)method with a three-layer scheme for the entry trajectory optimization of the cross-domain morphing vehicles(CDMVs).By defining the new morp...This paper proposes a hybrid sequential second-order cone programming(HSSOCP)method with a three-layer scheme for the entry trajectory optimization of the cross-domain morphing vehicles(CDMVs).By defining the new morphing rate control variable and using relaxation techniques to relax the bank angle constraint,the SOCP-based entry problem is constructed.A dynamic relaxation penal-ization technique is developed in the first layer to overcome artificial infeasibility and significantly enhance initialization robustness.A novel standard oscillation identification(SOI)method is proposed to precisely identify the iteration oscillations of basic SSOCP in the second layer,which can significantly improve the solution accuracy.A soft-trust-region strategy is applied in the third layer to eliminate oscillations and accelerate convergence.Simulation results of two scenarios demonstrate that the proposed SOI method effectively avoids non-standard oscillation interference versus traditional methods.The morphing aircraft can complete tasks better with a 7.01%and 10.43%reduction in heat load respectively compared to fixed-wing aircraft.The HSSOCP method can maintain accuracy while reducing computation time by 63.47%and 73.86%versus VATSSOCP.Monte Carlo simulations further validate the robustness.展开更多
This paper develops an Oscillation-avoidance-based Multistage Trust-region Sequential Convex Programming(OMTSCP)method for the highly nonlinear entry trajectory optimization problem of Cross-Domain Morphing Vehicles(C...This paper develops an Oscillation-avoidance-based Multistage Trust-region Sequential Convex Programming(OMTSCP)method for the highly nonlinear entry trajectory optimization problem of Cross-Domain Morphing Vehicles(CDMVs).The decoupling of states and controls for complex nonlinear dynamics is achieved by defining new control and state variables.A series of sub convex problems is formulated by successive linearization and discretization of the constraints.The proposed Trust-region Sequential Convex Programming(TSCP)scheme consists of three stages:an initial guess generation stage,a basic solution stage,and an optimal solution stage.An approach to penalize the dynamic relaxation is firstly developed to obtain an initial guess with considerable accuracy and significantly improve the robustness of the algorithm by overcoming the drawbacks of potential artificial infeasibility.The oscillation phenomenon of the TSCP method under rectangular trust region is then investigated,and a novel N-shape-based oscillation identification method is proposed to identify the oscillation accurately.Finally,an oscillation-avoidance method based on the sort trust-region is proposed to improve the convergence of the TSCP algorithm.Numerical comparisons of the proposed method and a typical TSCP method,as well as the morphing and fixed-morphing vehicles are provided to demonstrate the effectiveness and efficiency of the proposed method and the performance advantages of the morphing vehicle.The robustness of the method is further verified by Monte Carlo simulation.展开更多
基金supported by the National Natural Sci‐ence Foundation of China(Grant No.62306325)。
摘要During the use of robotics in applications such as antiterrorism or combat,a motion-constrained pursuer vehicle,such as a Dubins unmanned surface vehicle(USV),must get close enough(within a prescribed zero or positive distance)to a moving target as quickly as possible,resulting in the extended minimum-time intercept problem(EMTIP).Existing research has primarily focused on the zero-distance intercept problem,MTIP,establishing the necessary or sufficient conditions for MTIP optimality,and utilizing analytic algorithms,such as root-finding algorithms,to calculate the optimal solutions.However,these approaches depend heavily on the properties of the analytic algorithm,making them inapplicable when problem settings change,such as in the case of a positive effective range or complicated target motions outside uniform rectilinear motion.In this study,an approach employing a high-accuracy and quality-guaranteed mixed-integer piecewise-linear program(QG-PWL)is proposed for the EMTIP.This program can accommodate different effective interception ranges and complicated target motions(variable velocity or complicated trajectories).The high accuracy and quality guarantees of QG-PWL originate from elegant strategies such as piecewise linearization and other developed operation strategies.The approximate error in the intercept path length is proved to be bounded to h2/(4√2),where h is the piecewise length.
基金financially supported by Ministerio de Ciencia e Innovación projects SAF2017-82736-C2-1-R to MTMFin Universidad Autónoma de Madrid and by Fundación Universidad Francisco de Vitoria to JS+2 种基金a predoctoral scholarship from Fundación Universidad Francisco de Vitoriafinancial support from a 6-month contract from Universidad Autónoma de Madrida 3-month contract from the School of Medicine of Universidad Francisco de Vitoria。
摘要Every year, around the world, between 250,000 and 500,000 people suffer a spinal cord injury(SCI). SCI is a devastating medical condition that arises from trauma or disease-induced damage to the spinal cord, disrupting the neural connections that allow communication between the brain and the rest of the body, which results in varying degrees of motor and sensory impairment. Disconnection in the spinal tracts is an irreversible condition owing to the poor capacity for spontaneous axonal regeneration in the affected neurons.
基金Fourth Phase of the China's Lunar Exploration ProgramChina National Space Administration (D040103)+1 种基金National Natural Science Foundation of China (62394354)National Key Research and Development Program of China (2025YFF0513303).
摘要It is important for a lunar lander to possess a large divert capability during the final landing phase,as this can enhance the tolerance for flight deviations in the early phase or improve the obstacle avoidance performance.Therefore,when designing the powered descent trajectory,sufficient final phase divert capability should be reserved at the minimum propellant cost.To this end,a multi-phase trajectory programming(MPTP)method for powered descent with approaching phase divert capability is proposed.First,the entire powered descent trajectory is divided into the main braking phase and the approaching phase.The main braking phase is responsible for dissipating the majority of the initial velocity.The approaching phase is responsible for safely and precisely flying toward the landing site.It is nominally a vertical descent trajectory and possesses equal divert capability in all horizontal directions.Then,a constant-thrust linear tangent guidance(LTG)accounting for the lunar curvature is designed for the main braking phase.For the approaching phase,a variable-thrust lossless convex programming(LCP)guidance considering the constraints of tilt angle and glide-slope angle is developed.Subsequently,to connect the two phases and further optimize the propellant consumption throughout the entire trajectory,a method for determining the phase switching condition is proposed.The originally difficult-to-solve two-parameter optimization problem is decomposed into two more easily solvable subproblems,which are solved iteratively via a bilevel optimization framework.Finally,the divert capability of the proposed method is verified through numerical simulation.The programmed trajectory is basically consistent with the results of the pseudospectral method,with the difference in propellant consumption being only 0.006%.This method is suitable for the rapid iterative design of nominal trajectories for lunar lander powered descent in engineering applications.
基金supported by the National Natural Science Foundation of China(62322305,62495090,62495095)。
摘要This paper delves into the H∞optimal output regulation problem for continuous-time linear systems with an unknown system model.By integrating the internal model principle with optimal control,we derive an optimal control policy and a worst-case disturbance policy through the formulation and solution of a zero-sum game problem.Subsequently,leveraging adaptive dynamic programming,we propose a policy iteration learning algorithm capable of learning both the optimal control policy and the worst-case disturbance policy directly from system data.The existing algorithms necessitate an initial stabilizing policy,a full-rank condition,and the storage of historical data to guarantee algorithm convergence.In contrast,we design a dual policy iteration algorithm equipped with an online learning mechanism,thereby eliminating these additional prerequisites.Simulation results with an antonomous ground vehicle underscore the effectiveness of our proposed algorithm,and its superiority is further demonstrated through comparisons with existing methodologies.
基金support from the National Natural Science Foundation of China(No.12002372)the Young Elite Scientists Sponsorship Program by China Association for Science and Technology(No.2022QNRC001)the Natural Science Foundation of Hunan Province,China(No.2021JJ40674)。
摘要The operational demands of a wide range significantly exacerbate combustion instability issues within ramjet combustor.To suppress combustion oscillations,an open-loop control system utilizing Linear Genetic Programming(LGP)has been developed for a full-scale annular ramjet combustor.The LGP is used to generate control laws that include multi-frequency forcing.These laws are then transformed into square waves to actuate the solenoid valve,which modulates the kerosene supply for open-loop control.The results show that the duty cycle has little effect on instability amplitude,whereas an increase in frequency leads to a remarked reduction in combustion amplitude.After five generations evolvements,the pressure amplitude is reduced by 40.6% under the optimal control law generated by LGP.Furthermore,the machine learning process is depicted using a proximity map of control law similarity,with the search pathway visualized by the steepest descent.All individuals go forward to the upper left corner of the map with the evolution process,terminating at the optimal individual of the fifth generation.
摘要Natural convection in enclosures containing nanofluids has attracted significant attention due to its relevance in thermal management systems.In this context,this study presents a comprehensive numerical investigation of flow and heat transfer in a square cavity saturated with water-based CuO nanofluid having a centrally placed sinusoidal-shaped heated element.All the enclosure walls satisfy the no-slip velocity condition.Thermally,the vertical walls are kept at a cold reference temperature,the lower wall is partially heated at its center,and the remaining portions of the lower and entire upper walls are adiabatic.The internal sinusoidal element is also uniformly heated.The flow dynamics and thermal fields are governed by the two-dimensional steady-state Navier-Stokes and energy equations,solved using the Galerkin finite element method.Additionally,a novel hybrid approach integrating multi-expression programming(MEP)technique with a convolutional neural network bidirectional gated recurrent unit(CNN-BiGRU)deep learning network is also applied to enhance flow and thermal prediction accuracy.This hybrid approach enables precise evaluation of how heater waviness,magnetic field orientation,and nanoparticle dispersion influence flow structure and heat transfer.Results reveal stronger convection at high Rayleigh numbers,magnetic damping at increased Hartmann numbers,and higher temperatures with reduced velocity at greater nanoparticle concentrations.Among the analyzed situations,increasing heater waviness improves heat-transfer performance.Both the MEP and CNN-BiGRU models accurately capture the key features of flow and heat transport trends,indicating that the hybrid approach provides enhanced predictive capability for complex convection-driven nanofluid systems.
基金supported by the Open Fund of Laboratory of Aerospace Servo Actuation and Transmission(No.LASAT-2022-A03).
摘要This paper proposes a hybrid sequential second-order cone programming(HSSOCP)method with a three-layer scheme for the entry trajectory optimization of the cross-domain morphing vehicles(CDMVs).By defining the new morphing rate control variable and using relaxation techniques to relax the bank angle constraint,the SOCP-based entry problem is constructed.A dynamic relaxation penal-ization technique is developed in the first layer to overcome artificial infeasibility and significantly enhance initialization robustness.A novel standard oscillation identification(SOI)method is proposed to precisely identify the iteration oscillations of basic SSOCP in the second layer,which can significantly improve the solution accuracy.A soft-trust-region strategy is applied in the third layer to eliminate oscillations and accelerate convergence.Simulation results of two scenarios demonstrate that the proposed SOI method effectively avoids non-standard oscillation interference versus traditional methods.The morphing aircraft can complete tasks better with a 7.01%and 10.43%reduction in heat load respectively compared to fixed-wing aircraft.The HSSOCP method can maintain accuracy while reducing computation time by 63.47%and 73.86%versus VATSSOCP.Monte Carlo simulations further validate the robustness.
基金supported by the Open Fund of Laboratory of Aerospace Servo Actuation and Transmission,China(No.LASAT-2022-A03)。
摘要This paper develops an Oscillation-avoidance-based Multistage Trust-region Sequential Convex Programming(OMTSCP)method for the highly nonlinear entry trajectory optimization problem of Cross-Domain Morphing Vehicles(CDMVs).The decoupling of states and controls for complex nonlinear dynamics is achieved by defining new control and state variables.A series of sub convex problems is formulated by successive linearization and discretization of the constraints.The proposed Trust-region Sequential Convex Programming(TSCP)scheme consists of three stages:an initial guess generation stage,a basic solution stage,and an optimal solution stage.An approach to penalize the dynamic relaxation is firstly developed to obtain an initial guess with considerable accuracy and significantly improve the robustness of the algorithm by overcoming the drawbacks of potential artificial infeasibility.The oscillation phenomenon of the TSCP method under rectangular trust region is then investigated,and a novel N-shape-based oscillation identification method is proposed to identify the oscillation accurately.Finally,an oscillation-avoidance method based on the sort trust-region is proposed to improve the convergence of the TSCP algorithm.Numerical comparisons of the proposed method and a typical TSCP method,as well as the morphing and fixed-morphing vehicles are provided to demonstrate the effectiveness and efficiency of the proposed method and the performance advantages of the morphing vehicle.The robustness of the method is further verified by Monte Carlo simulation.